"Improving OKR Strategies" matching MCP servers:

MCP server for OCR.space API to extract text from images and PDFs, with tools for file, URL, automatic oversized handling, and language support.

Enables OCR-enabled PDF to Markdown conversion in Claude Code, with per-page inspection and hybrid handling of text, scanned, mixed, and blank pages via a local vision-model endpoint.

Provides structured OCR with verified bounding boxes using the space-ocr API. Allows extraction of structured fields from document images and listing of built-in templates.

Extracts text and images from PDFs and image files using the Mistral OCR API, with a security sandbox for file writes.

Enables MCP clients like Claude Code to extract text from images, screenshots, and scanned documents via PaddleOCR PP-OCRv6.

Provides OCR capabilities for images and PDFs using Yandex Vision API. Supports multiple recognition models and output formats.

Enables AI agents to convert images and PDFs, including large scanned books, into Markdown through GLM-OCR, with support for long-image slicing, progress tracking, and asynchronous OCR tasks.

Enables AI assistants to decode QR codes from images, with tools for scanning full images and enhancing blurry or reflective regions before decoding, plus quality diagnostics to guide retry strategies.

A Model Context Protocol server that gives AI assistants OCR with first-class accuracy handling and evaluation. It wraps three engines behind one interface and can score and compare them.

Extracts text from images and browser screenshots locally using Tesseract.js, without sending image data to the LLM.

Exposes local Umi-OCR v2 capabilities to AI agents via MCP, enabling image text extraction, batch OCR, PDF OCR, and status checks without manually starting the service.

Enables detection of AI-generated content in images, videos, audio, and text via the AI or Not API. Supports media analysis tools for deepfakes, synthetic voices, and AI-written text.

Enables text extraction from images and PDF files using the ZhipuAI GLM-OCR API. It allows users to process documents through local file paths or base64-encoded data for high-quality OCR results.

Enables AI agents to recognize and extract text from images using PaddleOCR, supporting both file paths and base64 input with structured results including confidence scores and text positions.

Extracts text content from PDFs and images using Mistral's OCR API, enabling OCR capabilities in MCP-compatible clients like Cursor and Claude Desktop.

Enables MCP clients to run OCR on local image files through a single long-lived PaddleOCR backend shared across clients, returning recognized lines as a Markdown table with optional coordinate and confidence columns.

A Tesseract.js-based server that enables image-to-text recognition within MCP-compatible environments like Cursor. It supports multiple languages and common image formats, allowing users to extract text from local files using natural language commands.

Enables OCR processing of local files and public URLs using Mistral OCR. Provides tools for health checks, key management, page listing, and generating Markdown output.

Enables agent frameworks to invoke OCR as a structured tool, supporting single images, multi-page images, and PDFs via local Transformers or remote vLLM/SGLang backends.

Enables document OCR processing via OcrPlane APIs, supporting document parsing, asynchronous polling, markdown extraction, and task management.